13 Predisposing, precipitating and perpetuating factors in functional neurological disorder: a pilot study
Bibliographic record
Abstract
Objectives/Aims Biopsychosocial perspectives have highlighted the multifactorial and diverse aetiology of functional neurological disorder (FND). We aimed to assess a range of potential predisposing, precipitating and perpetuating factors in FND, and to explore relationships between aetiological factors and current functioning or health-related quality- of-life (HRQoL). Methods Seventeen participants with FND (motor symptoms and/or seizures) and 17 healthy controls (HCs) underwent an in-depth interview and completed validated questionnaires, including the Traumatic Experiences Checklist (TEC), Toronto Alexithymia Scale-20, Multiscale Dissociation Inventory, Somatoform Dissociation Questionnaire-20, Autistic Spectrum Quotient, Patient Health Questionnaire-9 and -15, Generalised Anxiety Disorder-7, Brief Illness Perception Questionnaire (B-IPQ), Short Form Survey-36 (SF-36) and the Work & Social Adjustment Scale. Results The groups did not differ in sex (p=1.00) or age (p=.51). The most commonly reported FND symptom precipitants were physical activity/exertion (59%), stress/emotion (59%), sensory (47%) and fatigue (41%). Perceived causes of FND (B-IPQ) were physical (e.g., injury, illness, 65%), stress/emotions (53%), psychosocial trauma (47%) and work-related (29%). There was a trend towards higher rates of adverse life events (TEC) in the FND group compared to HCs (p=.06), and the FND group reported greater impact of events (p=.03). The most frequent adverse experiences in the FND group were: looking after parents/siblings as a child (41%), family problems (41%), parental divorce (41%), intense pain (41%), emotional neglect (41%), and sexual abuse (non-familial, 41%). The most common adverse experiences in HCs were: bereavement (35%) and parental divorce (41%). The FND group had higher scores for alexithymia (p=.002), somatoform dissociation (p<.001), aspects of psychological dissociation (disengagement p=.003, depersonalisation p=.001, derealisation p=.002, memory disturbance p=.01), anxiety (p<.001), depression (p<.001), and physical symptoms (p<.001). No significant differences were observed for autistic spectrum traits (p=.22) and some types of psychological dissociation (emotional constriction p=.38, identity disturbance p=.17). FND participants reported worse HRQoL than HCs in all SF-36 domains (p-values .01- <.001). Work/social functioning was impaired in the FND group relative to HCs (p<.001). Poorer work/social functioning was associated with higher depression scores (p=.016). Worse HRQoL in several domains was associated with higher somatoform dissociation and/or anxiety scores (p-values .044-.005). Lower general health HRQoL scores were associated with higher TEC total (p=.020) and impact (p=.011) scores. Conclusions Individuals with FND report diverse aetiological factors, including psychosocial, physical and environmental stressors. Alexithymia, dissociative tendencies, emotional distress, and physical symptom burden are also possible predisposing and/or perpetuating factors. Somatoform dissociation, anxiety and adverse experiences may be related to HRQoL in FND.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".